A privacy protection method and system for friend matching based on mobile social network second-degree contacts

Abstract

The invention discloses a friend matching privacy protection method and system based on the second-level network of a mobile social network, and the method comprises the steps: dividing user feature attributes into required attributes and optional attributes; carrying out the secret key negotiation through the required attributes and optional attributes of a making-friends sponsor and a making-friends responder, wherein only a making-friends requester who achieves the successful negotiation can enter a next precise optional attribute matching stage; solving the similarity of the feature attributes between two sides through the inner product of vectors, wherein the making-friends requester can serve as an agent for transferring a matched file, thereby extending the second-level network. Themethod employs the Chinese remainder theorem for mode calculation and secret key calculation, and each making-friends user manages the secret key by himself, so the method can effectively reduce thesecret key leakage risks of a single-attribute center, and also reduce the calculation expenditure in a matching process. For the matching of a personal attribute configuration file, the method guarantees the privacy of the user through the introduction of vector calculation and big prime number fuzziness while guaranteeing the precise matching.

Description

technical field [0001] The invention belongs to the field of computers, and in particular relates to a privacy protection method and system for friend matching based on mobile social network second-degree contacts. Background technique [0002] With the popularity of mobile terminal devices, mobile social networks (MSN) have developed rapidly. Through mobile social networks, people have a broader communication platform, meet new friends, and further expand their social scope. . For example, WeChat, Zhiquan, etc. that accompany us in our daily life. [0003] Users can find friends with common characteristics in the mobile social network by performing similarity matching on their own characteristic attributes. These characteristic attributes can include user identity, location, hobbies, etc.; The risk of information being leaked mainly includes: location privacy leak, identity privacy leak, data privacy leak, medical data privacy leak, etc. Once user privacy is leaked, it m...

AI Technical Summary

Problems solved by technology

[0008] Although the above solutions solve the credible problem of making friends to a certain extent, they still belong to strangers making friends. Therefore, in actual application scenarios, there are situations where the circle of friends making friends is unstable; in addition, the above solutions do not fully integrate the mobile social network. Features, taking into account the user's actual location information, so the scope of application is relatively limited, for example, when the user changes the location of making friends, it may be difficult to find friends with common characteristics

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